Optimization of Site-exploration Programs in Slope Designs Using 3D Conditional Random Fields

Abstract

Background: In situ soil properties exhibit inherent spatial variability, which is often described by a 3D random field. Soil properties at particular portions are available by site investigation. Wider site investigation scope provides a more accurate description of the geologic profile. However, limited by budget, choosing an effective site exploration scope is of significance. Objective: This study introduces a framework to determine the optimal site investigation strategy in the 3D domain, which yields the lowest mean risk of slope designs. Method: The mean risk of slope designs is considered to be a function of the costs of site investigation, under-design, and over-design. The unconditional random fields are generated by the spectral representation method initially. Subsequently, the sampled data are incorporated into the random fields via the Kriging algorithm, and the conditional random fields are simulated. A 3D undrained slope is evaluated for illustration. Results: The effects of sampling locations and spacing on the risk of slope designs are examined. The results indicate that the optimal sampling location is close to the zone where slope failure may occur. Moreover, there exists an optimal sampling spacing that minimizes the mean risk of slope designs. Conclusion: This investigation can provide guidance for determining the optimal site exploration programs on the 3D domain with knowledge of the associated risks.